Clearml

ClearML is an open, end-to-end AI infrastructure and MLOps platform designed to help teams manage, orchestrate, and scale machine learning and generative AI workloads. It centralizes experiment tracking, data and model management, and production pipelines while providing tools to efficiently utilize on-premise or cloud GPU resources. The primary purpose of ClearML is to give engineering and data science teams a unified control plane for the entire ML lifecycle, from research to large-scale deployment.

Key capabilities include experiment management with automatic logging of code, parameters, metrics, and artifacts, enabling full reproducibility and collaboration. ClearML provides a powerful orchestration layer for scheduling and automating training, evaluation, and inference pipelines across heterogeneous compute clusters, including Kubernetes and bare-metal GPU servers. It also supports model registry, versioning, and promotion workflows, as well as monitoring of resource utilization and job status through a web-based dashboard and APIs. Native integrations with common ML frameworks and CI/CD tools help embed ML processes into existing engineering workflows.